Search: “benchmark”

DepthTile: Depth-Guided Existing-Image Self-Tiling with Input-Side Tileability Assessment

arXiv:2610.16278v1 Announce Type: new Abstract: Existing-image self-tiling aims to transform a given image into a seamlessly repeatable tile while preserving its original semantics and local details.

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Research

Detecting Chain-of-Thought Hijacking in Backdoored Multimodal Large Reasoning Models

DGX agent

arXiv:2610.16598v1 Announce Type: new Abstract: Chain-of-thought (CoT) reasoning enables multimodal large reasoning models (MLRMs) to solve complex visual problems, but also exposes them to CoT hijack

researcharxiv-cs-cv

14 Oct 2026

Diversity You Can Actually Measure: A Fast, Model-Free Diversity Metric for Robotics Datasets

arXiv:2603.11634v2 Announce Type: replace Abstract: Robotics datasets for imitation learning typically consist of long-horizon trajectories of different lengths over states, actions, and high-dimensio

safetyarxiv-cs-ro

Do Artificial Neural Networks Need Dendritic Nanotubes? Two Reasons for Shrinking Importance Estimates in Continual Learning

arXiv:2610.14258v1 Announce Type: new Abstract: Regularization-based continual learning protects each parameter in proportion to an estimate of its importance, yet these estimates come from finite sam

Agents

DoubtLess: Training-Free Contrastive Decoding for Efficient Reasoning

arXiv:2610.18862v1 Announce Type: cross Abstract: Reasoning models achieve strong performance through long chains of thought (CoT), but often spend more tokens than needed to solve a problem. Existing

agentsarxiv-cs-lg

Agents

Dream2Discern: Learning from Hard Latent Variants for Runtime Failure Prediction in Multi-Agent Systems

arXiv:2610.16071v1 Announce Type: new Abstract: Reliable deployment of LLM-based multi-agent systems calls for runtime auditors that predict terminal outcomes from observed execution prefixes. These a

agentsarxiv-cs-lg

DSM-Free UAV Visual Localization via Latent-Depth Variable Projection and Structure-Adaptive Coupling

arXiv:2610.14945v1 Announce Type: new Abstract: Visual localization enables unmanned aerial vehicles (UAVs) to maintain absolute positioning in GNSS-denied environments. A common approach matches UAV

DuplexBridge: Coordinating Understanding and Generation for Unified Image Editing

arXiv:2610.18819v1 Announce Type: new Abstract: Complex image editing requires faithful task interpretation and accurate execution, but a failed edit does not reveal which responsibility failed. We pr

DVTR-KD: Distilling Vision-Language Models via Intermediate Visual Token Reconstruction

arXiv:2610.17853v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have achieved strong performance on diverse vision-language tasks, but their computational demands limit deploy

researcharxiv-cs-cv

DyJR: Preserving Diversity in Reinforcement Learning with Verifiable Rewards via Dynamic Jensen-Shannon Replay

arXiv:2603.16157v2 Announce Type: replace Abstract: While Reinforcement Learning (RL) enhances Large Language Model reasoning, on-policy algorithms like GRPO are sample-inefficient as they discard pas

local-aiarxiv-cs-lg

Dynamic Interpolation for Training-Time Prediction Reshaping in Low-Light Image Enhancement

arXiv:2610.18018v1 Announce Type: new Abstract: Low-light image enhancement (LLIE) is an important image/video processing problem for reliable visual systems under poor illumination, yet it remains ch

EAU: Environment-Agent-User Co-evolution for Training User-Centric Agents

arXiv:2610.16523v1 Announce Type: cross Abstract: Training LLM agents to interact with users over multiple turns is challenging because the learning signal depends not only on the agent, but also on t

Hardware

Echo: Error-Compensated 4-Bit Tensor-Parallel Communication for LLM Training and Inference

arXiv:2610.14277v1 Announce Type: cross Abstract: Tensor parallelism ends every layer with an all-reduce that sits between two dependent matrix multiplications, so its cost cannot be hidden and grows

hardwarearxiv-cs-lg

ECLIPTICA -- A Framework for Switchable LLM Alignment via CITA - Contrastive Instruction-Tuned Alignment

arXiv:2601.06157v2 Announce Type: replace Abstract: Alignment in large language models (LLMs) is still largely static: after training, the policy is frozen. DPO, GRPO methods typically imprint one beh

Agents

Efficient Multi-Agent Reasoning via Confidence-Guided Adaptive Debate

arXiv:2610.16343v1 Announce Type: cross Abstract: Multi-agent debate has shown promise for improving the reasoning of large language models, yet recent theory suggests its benefits are highly regime-d

agentsarxiv-cs-lg

Applications

Efficient Test-Time Adaptation through Latent Subspace Coefficients Search

arXiv:2510.11068v4 Announce Type: replace Abstract: Real-world deployment often exposes vision models to distribution shifts, making test-time adaptation (TTA) important for reliable prediction. Exist

applicationsarxiv-cs-lg

EgoCPT: Learning Dexterous Manipulation from a Single Ego-Centric Video with Contact-Aware Optimization

arXiv:2610.17572v1 Announce Type: new Abstract: While expert demonstrations on real robots are difficult to collect, human ego-centric videos are easy to collect and abundant on the internet. However,

researcharxiv-cs-ro

EgoMatrix: Physically Faithful Dexterous Robot Demonstrations from Egocentric Human Videos

arXiv:2610.18822v1 Announce Type: new Abstract: Egocentric human videos offer a scalable alternative to robot teleoperation for collecting dexterous manipulation data. However, two challenges limit th

safetyarxiv-cs-ro

EgoWholeView: Camera-Only Head-Mounted Capture of Body and Bimanual Hand Motion for Embodied Demonstrations

arXiv:2610.16256v1 Announce Type: new Abstract: Head-mounted body and bimanual motion capture supports self-avatars, teleoperation, and embodied demonstrations. However, a single egocentric camera is

ELECT: Settling Identity Before Rendering for Scalable Story Visualization

arXiv:2610.15555v1 Announce Type: new Abstract: Training-free story visualization without reference images must preserve recurring entities across frames while scaling to long narratives. Existing met

Elephant in the Fridge: Constant-Memory Frame Packing for Long Video Understanding

arXiv:2610.16118v1 Announce Type: new Abstract: Hour-long videos, streaming feeds, and movie-length content are pushing vision-language models (VLMs) past their breaking point -- the standard recipe o

Enabling Token-wise Importance Sampling in Off-Policy RLVR with Proximal KL Regularization

arXiv:2610.18738v1 Announce Type: new Abstract: Off-policy data in reinforcement learning with verifiable rewards (RLVR) can arise from asynchronous generation, rollout-training mismatch, and response

Encoding Context into LLM Weights: What Makes It Context?

arXiv:2610.17686v1 Announce Type: cross Abstract: Longer contexts allow large language models (LLMs) to condition their predictions on more information, but inference costs grow prohibitively with con

researcharxiv-cs-lg

Engram Neuron Inspired Adaptive Memorization for Lifelong Learning

arXiv:2610.14940v1 Announce Type: new Abstract: Lifelong learning enables artificial systems to adapt to changing environments. To achieve this, an effective artificial learner should dynamically reor

Ensemble-MIX: Enhancing Sample-Efficiency in Multi-Agent RL via Selective Ensemble-Based Exploration

arXiv:2506.02841v5 Announce Type: replace-cross Abstract: Multi-agent reinforcement learning (MARL) methods have achieved state-of-the-art results on a range of multi-agent tasks. Yet, MARL algorithms

EV-JEPA: Elastic V-JEPA for Any Device and Cross-Device Inference

arXiv:2610.14324v1 Announce Type: new Abstract: Foundation models like V-JEPA are increasingly deployed across a heterogeneous edge-cloud continuum spanning smart glasses, phones, robots, and servers.

local-aiarxiv-cs-cv

EventLens: Event-Structure Reinforcement Learning for Video Understanding

arXiv:2610.16172v1 Announce Type: new Abstract: Recent multimodal large language models (MLLMs) achieve strong results on video question answering, yet often fail to recover the temporal structure tha

safetyarxiv-cs-cv

Evidence-First Agentic Verification

arXiv:2610.17724v1 Announce Type: cross Abstract: Long-horizon, semi-verifiable agentic tasks often rely on rubric-based evaluation, but the evidence needed to assess these tasks can be spread across

EviScene: Beyond 'Is It AI?' for Agentic Image Factuality Assessment

arXiv:2610.14609v1 Announce Type: new Abstract: Determining whether an image is AI-generated does not establish whether the situation it depicts is factually supported. We formulate Image Factuality A

Exact Topological Compliance: Generating Persistence-Equivalent Graphs

arXiv:2610.18856v1 Announce Type: new Abstract: Persistent homology summarizes the topological evolution of a graph as persistence diagrams (PDs). Generating graphs whose topology matches a target des

researcharxiv-cs-lg

Explainable Visual Anomaly Detection via Concept Bottleneck Models

arXiv:2511.20088v3 Announce Type: replace Abstract: In recent years, VAD (Visual Anomaly Detection) has attracted significant attention due to its high interpretability, as it provides visual explanat

researcharxiv-cs-cv

Exploration strategies for Gaussian process bandit optimization with inference regret guarantees

arXiv:2610.16187v1 Announce Type: cross Abstract: Existing cumulative regret guarantees for Bayesian optimization (BO) do not necessarily characterize the quality of the algorithm's final output. This

researcharxiv-cs-lg

Explore with Memory, Learn without It: In-Context Exploration and Self-Distillation for LLM Reasoning

arXiv:2610.17734v1 Announce Type: new Abstract: Exploration bounds learning efficiency in reinforcement learning with verifiable rewards (RLVR). Current methods explore mostly through independent samp

Applications

Exploring the Latent Structure of AMD Severity Using Retinal Foundation Models

arXiv:2610.14138v1 Announce Type: cross Abstract: Retinal foundation models have demonstrated strong performance across a wide range of ophthalmic tasks, yet relatively little is known about how disea

applicationsarxiv-cs-cv

Exploring the Limits of Combinatorial Generalization in Embodied Manipulation

model-releasesarxiv-cs-ro

arXiv:2610.15425v1 Announce Type: new Abstract: In embodied manipulation, Vision Language Action (VLA) models can execute atomic skills, but long-horizon manipulation requires recombining these skills

Facial Recognition Leveraging Generative Adversarial Networks

arXiv:2505.11884v3 Announce Type: replace Abstract: Face recognition performance based on deep learning heavily relies on large-scale training data, which is often difficult to acquire in practical ap

Failure Recovery via Belief Updates and World Modeling for Long-Horizon Agents

arXiv:2610.18082v1 Announce Type: new Abstract: Long-horizon agents often struggle to recover from failures whose causes lie several steps earlier, beyond what local reflection or backtracking can res

local-aiarxiv-cs-lg

Federate the Router: Learning Language Model Routers with Sparse and Decentralized Evaluations

arXiv:2601.22318v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly accessed as remotely hosted services by edge and enterprise clients that cannot run frontier models lo

local-aiarxiv-cs-lg

FedLoRD: Personalized Federated Learning based on Low-Rank Structures of Model Parameter Differences

arXiv:2610.17621v1 Announce Type: new Abstract: We propose FedLoRD, a personalized federated learning (PFL) method based on the low-rank structure of the differences between the global and personalize

Fine-Tuning Strategy, Not Just Data: A Statistically Rigorous Audit of Gender and Stereotypical Bias in Embedding Models for HR Recommendation Systems

arXiv:2610.14579v1 Announce Type: cross Abstract: Embedding models underpin modern job-candidate matching: resumes, job descriptions, and queries are encoded as dense vectors, and recommendations come

FIRE: Multi-fidelity Regression with Distribution-conditioned In-context Learning using Tabular Foundation Models

arXiv:2601.22371v2 Announce Type: replace Abstract: Multi-fidelity (MF) regression often operates in regimes of extreme data imbalance, where the commonly-used Gaussian-process (GP) surrogates struggl

FireNav: Decision-Oriented Reconstruction Evidence Routing for Vision-Language Navigation in Indoor Fire Environments

arXiv:2610.15595v1 Announce Type: new Abstract: In real-world indoor fire environments, visual degradation severely impairs instruction grounding, waypoint prediction, and long-horizon exploration in

FlowAvatar: Real-Time Full-Body Avatars from Sparse Egocentric Inputs on Consumer XR Devices

arXiv:2610.16277v1 Announce Type: new Abstract: Prior avatar embodiment research has studied tracking completeness (how faithfully the body, hands, and face are sensed and reproduced) and personalized

FlowCred: Hierarchical Credit Assignment and Functional Coordination for Joint Text-to-Video Post-Training

arXiv:2610.18142v1 Announce Type: new Abstract: Prompt optimization and generator post-training are two complementary ways to improve text-to-video (T2V) generation, and recent systems increasingly tr

local-aiarxiv-cs-cv

FrameLite: Decision-Oriented Aesthetic Cropping with a Compact Vision-Language Model

arXiv:2610.17639v1 Announce Type: new Abstract: Aesthetic image cropping improves composition by balancing subjects, context, and image boundaries. Large vision-language models bring semantic knowledg

local-aiarxiv-cs-cv

Frequency Routing and Identity Conditioning for Thermal-to-Visible Face Translation

arXiv:2610.17859v1 Announce Type: new Abstract: Thermal-to-visible (T2V) face translation has important applications in nighttime biometric recognition, low-light surveillance, and human interpretatio

From Associations to Activations: Comparing Behavioral and Hidden-State Semantic Geometry in LLMs

arXiv:2602.00628v3 Announce Type: replace Abstract: We investigate the extent to which an LLM's hidden-state geometry can be recovered from its behavior in psycholinguistic experiments. Across eight i

From bits to atoms: A survey of cross-layer safety in Embodied AI

arXiv:2610.14038v1 Announce Type: new Abstract: Embodied Artificial Intelligence (AI) introduces cyber-physical risks because digital failures and attacks can cause physical harm. This survey organize

safetyarxiv-cs-ro